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The Near-real-time Ice and Snow Extent (NISE) data set provides daily, global maps of sea ice concentrations and snow extent. These data are not suitable for time series, anomalies, or trends analyses. They are meant to provide a best estimate of current ice and snow conditions based on information and algorithms available at the time the data are acquired. Near-real-time products are not intended for operational use in assessing sea ice conditions for navigation.

1. Detailed Data Description

Format

The NISE product is updated daily
using the best available data from the past five days. Data are in Hierarchical
Data Format - Earth Observing System (HDF-EOS) format and browse files are
in GIF and HDF formats. HDF-EOS data files are available from 04 May 1995 through
the present. Data in both formats are updated daily.

Daily data are provided in a single HDF-EOS file containing
four grid objects: one data grid and one age grid each for both the Northern
and Southern hemispheres. The data grids contain snow extent, sea ice concentration,
and coastal (mixed) pixels. The age grids contain the age of input data
in days (from day of data acquisition to map production) relative to the
date of the daily file. Values are stored in the data and age grids as binary
arrays of unsigned 1-byte (8-bit) data ranging in value from 0 to 255.

File Naming Convention

Files are named according to the following conventions and
as described in Table 1:

File Size

Spatial Coverage

Spatial coverage is shown in Figures 3 and 4, and is global except for a gap
of three degrees latitude from each pole (87 to 90 degrees latitude). The application of monthly-varying masks limits the mapped extent of snow and sea ice in both hemispheres.

Spatial Coverage Maps

Figure 3.
Northern Hemisphere

Figure 4.
Southern Hemisphere

Spatial Resolution

The spatial resolution for this data set is 25 km.

Projection and Grid Description

Sea ice concentration and snow extent maps are
provided in two azimuthal, equal-area projections: the Southern Hemisphere
25 km low resolution (SL, indicating Southern Low) and Northern Hemisphere 25 km low resolution (NL, SL, indicating Northern Low)
Equal-Area Scalable Earth-Grids (EASE-Grids). See All About EASE-Grid for more information about the equal-area projections used for this product. Grids are 721 columns by 721 rows. The respective pole is aligned with the center of the pixel at the center of the grid.

Temporal Coverage

For each 24-hour period, NISE is updated using the most recent
data for a given grid cell. The frequency of updates varies as a function of
latitude. Grid cells representing latitudes above 55 degrees or below -55 degrees,
for which multiple satellite passes are available each day, are usually updated
every 24 hours. Due
to the orbital geometry of the DMSP satellite and the swath width of the SSM/I
sensor, the time interval between successive observations at low-latitude locations
(-20 to 20 degrees) can be up to five days (Hollinger et al. 1987). Problems
are not anticipated with this low-update frequency given the absence of sea
ice and very limited snow extent at these low latitudes. During occasional
periods when input data are unavailable or unobtainable, the NISE product age
values at any location may be older than five days. An age grid indicates the
number of days since each grid cell was last updated (see Data
Acquisition Methods).

Temporal Resolution

Each HDF-EOS file represents daily data comprising the last available snow extent or sea ice concentration data for each pixel.

Parameter or Variable

Parameter Description

Table 2 lists data values and the following parameters used in
the data grids:

Snow extent: Presence or absence of snow

Sea ice concentration: Sea ice concentration (percent)

Coastal pixel: 100-km-wide area of grid cells comprising the mixed pixel regions along a coastline

Table 3 lists data values and the following parameter used in the
age grids:

Age: Age of input data used to derive a corresponding data grid value, in days relative to the date of the daily file

Table 3. Age Grids

Data Value

Parameter

0-254

Age in days since date of file

255

Filler value for corners (off-Earth) and undetermined data pixels

Parameter Range

Cell values range from 0 to 255 for snow extent, sea ice concentration, and age grids.

Sample Data Records

Figures 1 and 2 show snow extent, sea ice concentration, and age layers for 03 February 2002 for the Northern and Southern Hemispeheres, respectively.

Figure 1.Sample data record for NISE_SSMIF13-20020203_N.GIF.

Figure 2.Sample data record for NISE_SSMIF13-20020203_S.GIF.

Error Sources

Physical conditions affecting the accuracy
of the sea ice concentration algorithm include atmospheric water content, ocean roughening and spray, presence of thin ice, and formation of melt ponds on the sea ice. Errors become greatest during mid- to late summer, resulting primarily from melt ponds on the ice surface, and also from atmospheric- and weather-related effects over open ocean. To minimize the error over open ocean, a filter is applied to detect these atmospheric effects. False ice concentration estimates may also occur along coastlines due to mixed pixels. Mixed pixels contain signals from both land and water in unknown proportions. For the NISE product, such errors are minimized by designating these pixels as coastal pixels.

The snow extent mapping algorithm maps a grid cell as snow-covered when it has a computed snow depth greater than 2.5 cm.

The presence
of dense coniferous and deciduous forests presents problems for mapping snow
extent with SSMIS because the vegetation canopy obscures snow on the ground.
The best conditions for accurate snow extent mapping using SSMIS are in
areas of little or no vegetation such as in the prairies and tundra.

Quality Assessment

Quality control for this product is performed by the
National Environmental Satellite, Data, and Information
System (NESDIS) when
converting Temperature Data Records to brightness temperatures. NSIDC visually
inspects daily NISE browse files.

Confidence Level/Accuracy Judgment

The accuracy of the sea ice concentration estimates is within
approximately five percent in most areas during the majority of the year.
For the sea ice component of the current NISE Version 4 product, NSIDC has
done preliminary inter-calibration between F13 and F17 to correct for the
sensor differences using an overlap period of 28 March 2008 through 28 March
2009.
F17 sea ice estimates should be reasonably consistent with F13 estimates,
although differences of approximately 28,000 sq km may be possible in daily
total extents. The differences are primarily near the ice edge, where shifts
of one to two grid cells (25-50 km) may be seen.

Version 4 of NISE incorporates a spillover correction (Cavalieri
et al. 1999) that reduces or eliminates sea ice concentrations
near coastlines when there is open water present. Due to the relatively large
microwave footprint size, passive microwave emissions from adjacent land
masses contaminate the signal for coastal pixels, producing spurious sea
ice extents in coastal regions that are actually void of sea ice, especially
during summer months.
In addition, due to slight sensor differences, NISE
Version 4 sometimes shows a higher number of pixels with a sea
ice concentration value of 100 percent than the NISE Version 2 product.
A one-year overlap period of NISE Version 4 data is available upon request
for comparison with NISE Version 2 data. Please contact NSIDC
User Services to access these data.

Armstrong and Brodzik (2001) demonstrate
that the snow extent algorithm can provide daily global snow extent maps
to an accuracy of approximately 50 km, except in areas of wet snow or dense
forest cover. In the snow extent product, when the snow is wet -- when liquid
water is present on the snow grain surface -- the snow pack becomes predominantly
an emitter and much of the scattered portion of the ground signal is lost,
greatly limiting algorithm accuracy. To reduce the frequency
of observations over wet snow, only data from the early morning
(descending) orbits are used as input to the algorithm.
The Version 4 snow extent algorithm uses F17 brightness temperatures that have
been adjusted with a linear regression to F13 brightness temperatures over
selected stable targets for the period of 28 March 2008 to 28 March 2009.

2. Data Access and Tools

Get Data

Direct Data Access

Important: Whereas the Other Data Access Options listed in Table 5 either automatically
register a user through the data ordering process or through the creation
of a user account, accessing the data via FTP provides an Optional
Registration Form for the user to complete. Since registered users
receive e-mail notification regarding important product changes, data users
are encouraged to register for the data.

Other Data Access Options

Users may also obtain NISE data by searching and ordering
via Reverb, or by subscription. Table
5 lists the Web site link to each data source and also gives an
explanation as to what each data source offers.

Search and discover data from NSIDC and other Earth Observing System Data and Information System (EOSDIS) data centers. Designed to work with ECHO, the Earth Observing System (EOS) Clearing House, Reverb also offers functions such as parameter and spatial subsetting.

Subscribe to have new EOS data sets automatically sent via FTP to
a local server, or staged on NSIDC's FTP site for FTP pull download.

Software and Tools

The EASE-Grid Geolocation Tools Web page provides files containing arrays of latitude and longitude values for each grid cell. Fortran and C source code are available for converting grid cell locations to latitude and longitude values, and vice-versa. An Interactive Data Language (IDL) program is available for converting latitude and longitude values to grid column and row coordinates.

3. Data Acquisition and Processing

Sensor or Instrument Description

NSIDC creates the current NISE product
using passive microwave data from the Special Sensor Microwave
Imager/Sounder (SSMIS) on board the Defense Meteorological
Satellite Program (DMSP) F17 satellite. The SSMIS instrument
is the next generation Special Sensor Microwave/Imager (SSM/I) instrument.

The SSMIS sensor is a conically-scanning passive microwave
radiometer that harnesses the imaging and sounding capabilities of three
previous DMSP microwave sensors, including the SSM/I, the SSM/T-1 temperature
sounder, and the SSMI/T-2 moisture sounder. The SSMIS sensor measures
microwave energy at 24 frequencies from 19 to 183 GHz with a swath width
of 1700 km. Refer to
the SSMIS
Instrument Description Web page for more details.

Data Acquisition Methods

The Fleet Numerical Meteorology and Oceanography Center (FNMOC)
first receives SSMIS raw antenna temperatures.
Data are then sent to NESDIS where they are processed into swath brightness
temperatures (TBs). NSIDC obtains these swath TBs
via FTP once per day from the NESDIS Comprehensive Large Array-data Stewardship
System (CLASS), typically within two to four days of the satellite overpass.

The NISE product provides a best estimate of current ice and
snow conditions based on information and algorithms available to NSIDC at
the time the product is created. If new input data from CLASS are
unavailable or unobtainable, then NSIDC has no new information with which to
update the NISE product. The current day's data layers will be identical
to those of the previous day, and the age layers will be incremented by
one day.

Problems obtaining the input data are usually resolved within one
business day; however, if new input data are unavailable or unobtainable for
five days in a row, NISE data production is halted until the problem is
resolved. The NISE product is then reprocessed from the beginning of the
interruption, and the new data are released.

Data Sources

NISE Version 2 data originate
from the SSM/I sensor onboard the DMSP-F13
satellite, and NISE Version 4 data originate from SSMIS onboard
the DMSP-F17
satellite. Note: No
NISE Version 3 product is available.

Derivation Techniques and Algorithms

All algorithms are subject to change in order to provide the best
possible snow and ice mapping capabilities. Snow extent derived from passive
microwave satellite data is a product that is constantly undergoing revision
and improvement at NSIDC.

Sea ice concentration
percentage for the NISE
Version 4 product is derived using the NASA
Team total sea ice (first year ice plus multiyear ice) algorithm (Cavalieri
et al. 1992). For
sea ice, all SSMIS (19, 22, and 37) GHz data from
a given 24-hour period are binned to the EASE-Grid using a "drop-in-the-bucket" interpolation
method. For snow extent mapping, TB values
from the satellite's morning pass only are used as input to the nearest neighbor
interpolation. Regions for which the respective interpolation algorithm will
be used are defined using a land/ocean/ice cap mask.

Snow extent is mapped separately using an algorithm developed for
Scanning Multichannel Microwave Radiometer (SMMR) data as described in Chang,
Foster, and Hall (1987), and modified for use with SSM/I data
as described in Armstrong
and Brodzik (2001).
NSIDC modified the snow extent mapping algorithm in March 2002, based primarily
on a recent study by Armstrong and Brodzik (2002).
One goal of this study was to determine when the differences between microwave
algorithm output and the validation data are random and when they are systematic;
therefore, this study made use of larger and more comprehensive validation
data sets that could provide a full range of snow/climate conditions, rather
than limited data that might only represent a snapshot in time and space.

Armstrong and Brodzik evaluated snow extent derived from passive microwave data through comparison with over ten years of the NOAA Northern Hemisphere snow charts, which are based on visible-band satellite data. Results clearly indicated time periods and geographic regions where the two techniques agreed and where they tended to consistently disagree. While not always an exact representation of the actual snow extent, the NOAA snow maps are highly accurate and are the product of a well-understood analysis procedure, and as such they were considered truth in these comparisons. The algorithms compared represented examples that included both mid- and high-frequency channels, vertical and horizontal polarizations, and polarization difference approaches, thus allowing an evaluation of the relative merits of these different approaches at the hemispheric scale.

This study demonstrated that both the new NSIDC NISE algorithm and the original Goodison (1989) algorithm underestimated snow extent in the presence of shallow snow; however, during winter and spring the Goodison algorithm tended to consistently overestimate the snow extent (both wet and dry snow) in various locations -- in particular, over such regions as the high-elevation deserts of Central Asia. Armstrong and Brodzik concluded that this was most likely due to an enhanced spectral gradient of the vertical polarization channel in the presence of frozen desert soils. Similarly, the 37 GHz polarization difference that drives the wet snow algorithm often responded to the soil types in this region such that it caused a false snow signal.

In summary, this study indicated that horizontal-polarization-based algorithms, while apparently underestimating snow extent during early winter, appear to provide the best overall estimates of snow extent at the continental to hemispheric scale through the period of maximum snow extent and into the melt season. Vertical-polarization-based algorithms (Goodison 1989) provide similar results but with a consistent tendency to falsely identify snow-free desert soils and/or frozen ground as snow-covered.

The snow extent climatology for the Northern Hemisphere is a monthly mask derived from the Northern Hemisphere EASE-Grid Weekly Snow Cover and Sea Ice Extent from October 1966 to May 2005. Beginning 01 July 2005, the snow extent climatology for the Southern Hemisphere is a monthly mask derived from the SSM/I period data from 1987 to 2003, identifying by month those parts of South America and New Zealand that may be snow-covered during that month. The original Southern Hemisphere snow climatology was a static file (not monthly) that served as a spatial representation of the expected snow line in the Andes as a function of latitude and elevation to determine snow extent (Schwerdtfeger 1976). NISE files dated 30 June 2005 and earlier use the original mask.

Northern Hemisphere Monthly Snow Extent Climatologies

Click on any thumbnail to see the full-resolution image.

January

February

March

April

May

June

July

August

September

October

November

December

Southern Hemisphere Monthly Snow Extent Climatologies

Click on any thumbnail to see the full-resolution image.

January

February

March

April

May

June

July

August

September

October

November

December

Northern Hemisphere Monthly Sea Ice Climatologies

Click on any thumbnail to see the full-resolution image.

January - June

July - December

Southern Hemisphere Monthly Sea Ice Climatologies

Click on any thumbnail to see the full-resolution image.

January - June

July - December

Version History

Table 6 outlines the processing and algorithm history for this product.

Reprocessed NISE Version
4 to include sea ice concentration values of 1-14%

This revision is an update to NISE Version 4. All
Version 4 data (17 August 2009 - present) have been reprocessed
with this system.

V4

2009-08-28

Changed input processing stream from the SSM/I instrument on board the
DMSP-F13 satellite to the SSMIS instrument on DMSP-F17

Changed input processing stream from NASA GHRC to NOAA CLASS

Conducted inter-calibration between F13 and F17 to correct for sensor
differences using an overlap period of 28 March 2008 - 28 March 2009;
adjusted tie points for the sea ice component of NISE; adjusted the snow
extent algorithm component of NISE.

Updated metadata field values for VERSIONID, LOCALVERSIONID and PGEVERSION

Changed definition of one day from orbit boundaries to UTC time; thus,
changed algorithm to determine one day of input data using midnight to
midnight UTC, rather than orbit boundaries. Previous versions of NISE
determined the beginning of a day with the first complete orbit past
midnight, and completed the day with the last orbit prior to midnight.

This revision is designated NISE Version 4. All data from 17 August 2009
to the present have been processed with this system. The NISE Version 2
product from F13 has been produced through 31 August 2009. (No
NISE Version 3 product is available).

V3

N/A

NA; no
NISE Version 3 product is available.

V2

2008-10-06

Ported NISE processing system from SGI to linux. No significant changes
in output.

V2

2006-04-27

New Northern Hemisphere snow climatologies with data from 1966-2005, and new Northern and Southern Hemisphere ice climatologies with data from 1979-2003.

V2

2005-07-01

Static Southern Hemisphere snow climatology limiting possible snow to the Andes region was replaced with a monthly climatology that now includes the Andes and New Zealand.

V2

2005-06-10

Data from the start of the SSM/I F13 mission (04 May 1995) to 31 December
1999 were processed to NISE Version 2.

V1

2005-04-25

A new LOCI mask was used, based on the Boston University (BU)-MODIS land cover
data set

Updated HDF libraries from HDF 4.1r1 to 4.1r3

Updated metadata field values for VERSIONID, LOCALVERSIONID
and PGEVERSION

Corrected error in browse images that was painting pixels
blue at the edge of the snow pack

This revision is designated NISE Version 2. All data from 01 January
2000 to present have been reprocessed with this system. NISE Version
1 files will be deleted at a future date.

Applications

This data set was originally designed to provide NASA EOS researchers
with near-real-time daily, global snow extent and sea ice concentration
data. The following NASA EOS instrument teams use the NISE data to generate
their products:

Multi-angle Imaging SpectroRadiometer
(MISR). The MISR instrument is part of a suite of sensors on NASA's
EOS Terra satellite. The NISE
product will be used as ancillary data for the MISR Top-of-Atmosphere/Cloud
product, which requires near-real-time daily, global snow and sea ice
extent data.

Clouds and the Earth's Radiant Energy System (CERES). CERES requires both daily and monthly averaged global snow and ice extent maps for several of their Earth radiation budget products. CERES is currently part of the Tropical Rainfall Measuring Mission (TRMM) aboard the EOS Terra platform.

Related Data Collections

Sea Ice Products

Sea Ice Data
at NSIDC offers a complete summary of sea ice data derived from passive
microwave sensors and other sources. It is useful for users who want to compare
characteristics of various sea ice products to understand their similarities
and differences. This site also provides links to tools for passive microwave
data and a list of other sea ice resources.